1st International Workshop on Teaching Decision Sciences and Technologies
February 9-10, 2012
Teaching Six Sigma Quality with R
Emilio L. Cano, Javier M. Moguerza, Andres Redchuk
emilio.lopez@urjc.es, javier.moguerza@urjc.es, andres.redchuk@urjc.es
Abstract: In this work, we show how we are joining Six Sigma and R software with
applications in teaching Decision Sciences and Technologies, allowing the inclusion of
emerging trends as open access and active learning using new technologies and explaining
innovative methods of teaching and assessment, such as automatic generation of exams or
reproducible results materials. We also describe our experience in implementing it within a
course of Quality Six Sigma of the VRTUOSI project.
Keywords: Six Sigma, Software R, Teaching, E-learning, Open Source.
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Introduction
Decision Sciences and Technologies entail a wide set of methodologies and tools
suitable for many disciplines, including politics, research or business management
among others. Statistics appear during the application of decision making one way
or another.
In this work, we show how we are joining the Six Sigma methodology [3] and the
R software [4] with applications in teaching Decision Sciences and Technologies
using innovative methods of teaching and assessment.
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The Six Sigma Paradigm
Six Sigma is a quality methodology for process improvement, whose main
strength is its ability for translating the complicated scientific terminology into an
easy way to apply science to quality improvement within organisations. As it
implies the use of statistics and science, we consider it is one of the Decision
Sciences and Technologies fields of application. Moreover, it can be used in
corporate environments (for both production and services) and in public services,
including education or healthcare. The basis of the Six Sigma methodology is the
DMAIC Cycle (Define, Measure, Analyze, Improve and Control. The DMAIC
cycle and other Six Sigma key concepts are introduced in the paper.
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Teaching Six Sigma Quality with R
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The R Choice
R is a system for statistical computing and graphing. It comprises a language, and
a software environment. The R system has being increasingly used in academia
and research from its beginning, and it is becoming a real alternative to
commercial software in corporate environments. The R system is open source, and
it is available for a number of platforms and configurations. The advantages of
using R for teaching Decision Sciences and Technologies are reviewed in the
paper, along with its reproducible research capabilities.
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Teaching Resources
Some teaching resources are referred in the paper from the author's successful
experience. The “Six Sigma with R” book [2] contains a Use Case and a number
of reproducible examples to enhance active learning. The SixSigma R package [1]
available at CRAN1 comprises functions and data sets for both learning and
applying Six Sigma using R. Finally, a guide for preparing homogeneous and
coherent materials, assignments and exams mixing R and LaTeX is outlined.
Acknowledgements
This work was supported by VRTUOSI project, www.vrtuosi.org, within the
Virtual Campus methodological framework of the EU Lifelong Learning
Programme (LLP, code 502869-LLP-1-2009-ES-ERASMUS-EVC)
References
[1] E. L. Cano, A. Redchuk, and J. M. Moguerza. SixSigma: Six Sigma Tools
for Quality Improvement, 2011. R package version 0.5.0.
[2] E. L. Cano, A. Redchuk, and J. M. Moguerza. Six Sigma with R. Statistical
Engineering for Process Improvement. Manuscript in preparation.
[3] M. Harry and R. Schroeder. Six sigma: the breakthrough management
strategy revolutionizing the world’s top corporations. Doubleday Business,
1999.
[4] R Development Core Team. R: A Language and Environment for Statistical
Computing. R Foundation for Statistical Computing, Vienna, Austria, 2011.
URL http://www.R-project.org/. ISBN 3-900051-07-0.
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The Comprehensive R Archive Network (http://cran.r-project.org)
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